+ the specification of software on our PC +
the Windows system

the applications
- ZEN black: ZEISS microscope application
- imgeJ/Fiji:open source application to process image
- Spyder: IDE for python code
- sikulix: automation platform
- Google Chrome: the Gmail web-portal is open and used by siulix to send messages if necessary.

step-by-step tutorial
1> prepare sample slide
prepare the cell or tissue culture on a coverslip.
mount it with 1 μM biotin-benzophenone in 50:50 DMSO:water and store in dark.
- the biotin-benzophenone is photo-active under two-photon excitation at 720 nm
2> photo-labeling on microscope
2.1 load the slide on microscope (we use zeiss LSM 880) and use 25x oil immersion lens.
2.2 start the applications on Windows:
2.3 setup the tiles
the workflow
please check the video
2.3.1 find the boundary points along the coverslip.
move along the edge of the coverslip. Stop at a location and manually focus on the sample.
add the location to the ‘Positions’ Panel.
keep going until 6~8 locations are collected.
save the boundary position list.
2.3.2. calculate the tiles within the shape refined in the boundary points.
call the script “tileScanConvexHullz_split.py” in Spyder
line 12: enter the path of the pre-saved “.pos” file of the boundary list
line 14: enter value of the tile size, always NOT smaller than of the scale of field of view. i.e. 25x lens on our LSM 880, the size of each field is 340.1 μm.
line 16: the maximum numbers of tiles can be written into a position file.
ZEN black may freeze when a positioin file contains more than 120 positions is loaded.
run the script “tileScanConvexHullz_split.py” after the parameters are entered.
position files are generated: “tilePos-1.pos”, “tilePos-2.pos”, “tilePos-3.pos”,…
the position file is loaded into Zen black in the “Positions” panel

2.3.3. setup the imaging parameters
load a position file, move to a tile position, then tune the laser powevr, receiver gain, and etc. to get an image with decent signal.
test 1~2 tiles. Then the imaging parameters are settled.
warning: close all active images in Zen black after the test.
2.3.4. call imageJ/Fiji
install the Fiji macro used for mask generation
“self.ijm” and “donut.ijm” are provided

the imageJ macro: “donut.ijm” is loaded

test processing images acquired in step 2.3.3. make sure the ijm macro works properly.
warning: after test, close all active images and windows by calling the macro “clearWindows”.
2.4 automation with the sikulix code
3> count the pixels STOMPed
3.1 the images and log files are organized into the folders by the order of the position files generated at the step 2.3.2.
3.2. run the python code “TotalPixels_allLogs.py” in Spyder.
line 15: enter the path of the parent folder generated at step 2.4.1.

the script will iterate through all its subfolder and collect and summarize the total pixels.

3.3 Typically, labeling 4~5 million pixel with mask resoution: 512x512 pixel-by-pixel under 25x lens should render sufficient proteins for one sample for Mass Spec submission.
four days per sample on the microscope is required.
4> lift the STOMPed coverslip and reserve it
4.1 unload the slide from the microscope once the STOMPing is finished. Clean the immersion oil, then soak the slide in the pure water for more than half an hour on a shaker.
4.2 gently peel off the seal around the coverslip, and transfer the coverslip with the sample to a parafilm.
4.3 rinse the coverslip with 50:50 DMSO:water 3 times, then rinse it with water 3 times. Dry in the air for 3 min, then reserve it in -30 degree C freezer. The sample is stored until preparing the lysate for Mass Spec analysis.